---
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-3_60-samples_config-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Mistral-7B_task-3_60-samples_config-2

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9100

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 3.6443        | 0.6957  | 2    | 3.4455          |
| 3.1998        | 1.7391  | 5    | 1.8330          |
| 1.1687        | 2.7826  | 8    | 0.7476          |
| 0.7861        | 3.8261  | 11   | 0.5044          |
| 0.3983        | 4.8696  | 14   | 0.4260          |
| 0.359         | 5.9130  | 17   | 0.3850          |
| 0.2531        | 6.9565  | 20   | 0.3752          |
| 0.1449        | 8.0     | 23   | 0.4619          |
| 0.1711        | 8.6957  | 25   | 0.5146          |
| 0.0704        | 9.7391  | 28   | 0.6076          |
| 0.0479        | 10.7826 | 31   | 0.7174          |
| 0.0096        | 11.8261 | 34   | 0.8062          |
| 0.0056        | 12.8696 | 37   | 0.8766          |
| 0.0024        | 13.9130 | 40   | 0.9100          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1